Space-occupying lesions identification in mammary glands using a mixed computational strategy
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Fecha
2019
Autores
Vargas, S
Vera, M I
Vera, M
Salazar-Torres, J
Huérfano, Y
Valbuena, O
Gelvez-Almeida, E
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Editor
IOP Publishing
Resumen
Abstract. The mammary pathology can manifest itself in multiple ways and originates spaceoccupying
lesions. The breast cancer is a space-occupying lesion, which is highly prevalent,
especially in women, and worldwide it is one of the leading causes of morbidity and mortality
in this population. The main image modality for breast cancer detection is the magnetic
resonance but this kind of image modality introduces several imperfections that affect the
image quality. Some of these imperfections or problems are: inhomogeneity in the anatomical
structures, riccian noise and artifacts. These problems make the analysis of the image
information a real challenge. To address these problems, in this paper, we propose a
computational technique able to extract a space-occupying lesion linked to breast cancer,
present in magnetic resonance images. For this, the original image is processed with statisticalarithmetic
filters and segmentation algorithms based on thresholding and multi-seed region
growing techniques. The results, based on Dice score, show that the proposed technique is
suitable for segmenting the breast cancer due high correlation between semi-automatic and
manual segmentations. This technique can be useful in the detection, characterization and
monitoring of this type of cancer and it can let to medical doctors to realize their work more
efficiently.
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Palabras clave
Mammary pathology, Breast cancer, Magnetic resonance images